This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The S.A.G.E. (Statistical Analysis for Genetic Epidemiology) computer program package provides researchers with the tools necessary for various types of statistical genetic analysis of human family data. Prior to the funding of this resource, few such computer programs were available, and those in existence were usually poorly documented and not easily transportable from one type of computer to another. This subproject has addressed these problems by developing computer programs for genetic analysis that are well documented and portable between different computers and operating systems. S.A.G.E. version 6.0 was released in January, 2009 and new releases of the software are posted, on average, twice per year. The program is constructed from compiled C++ code and runs on Windows, Unix/Linux, Solaris and MacOS platforms. The software includes a Java-based graphical user interface (GUI) designed to eliminate the need for new users to learn the complex syntax for program configuration. At the same time, advanced users may still create and analyze very sophisticated models using either the GUI or the more traditional command line version of the software. New features in version 6.0 include a completely new program, RELPAL, designed to perform model-free linkage analysis of a multivariate trait using all relative pairs. Significant improvements were made to the ASSOC program to make it better suited for analyzing large SNP data sets. Lastly, the S.A.G.E. source code was made available under the Berkley open source license. The next major release (version 6.1) is expected to include a new utility for managing high-throughput marker phenotypes, joint segregation and linkage analyses, and an efficient, generalized simulation program. A major redesign of S.A.G.E. is currently under consideration with the goal of making the software better integrated with the internet, and supporting collaboration between investigators using a common database.